CN104915785A - Power grid enterprise renewable resource price evaluation method based on social fair value - Google Patents
Power grid enterprise renewable resource price evaluation method based on social fair value Download PDFInfo
- Publication number
- CN104915785A CN104915785A CN201510336694.0A CN201510336694A CN104915785A CN 104915785 A CN104915785 A CN 104915785A CN 201510336694 A CN201510336694 A CN 201510336694A CN 104915785 A CN104915785 A CN 104915785A
- Authority
- CN
- China
- Prior art keywords
- price
- materials
- regenerated resources
- goods
- renewable resource
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
The invention provides a power grid enterprise renewable resource price evaluation method based on social fair value, which comprises steps: (1) a base year is selected, a future price and a spot price of each renewable resource at a historical sample interval, and a historical price of the same period of the renewable resource in a renewable resource trading market are read; (2) on the basis of a regression model, an intrinsic value evaluation model for the renewable resource is built; (3) a trend model for the renewable resource value evaluation model is obtained through a time difference and regression forecasting method; and (4) the renewable resource value evaluation model is applied, and accuracy of the model is checked. Through enhancing intrinsic value evaluation and extrinsic price forecasting, a renewable resource disposal evaluation and price calculation model based on the fair value is built for the system, application of the price evaluation model greatly enhances the efficiency of the renewable resource disposal work and management effects; and as for the national power grid and other industries such as mineral and building, renewable resource price evaluation has high theoretical and practical values.
Description
Technical field
The present invention relates to technical field of resource recovery, be specifically related to national grid business regeneration resource price appraisal procedure.
Background technology
State Grid Corporation of China's regenerated resources goods and materials concentrate science and the rationality of price potential in disposal activity of bidding, and are to promote regenerated resources goods and materials to be manipulated so power, the precondition of anti-scope mark string bid behavior and important guarantee.Carry out regenerated resources goods and materials and dispose price potential, to be worth regenerated resources goods and materials itself on the one hand and accurately calculate, particularly the analysis that large hybrid metal regenerated resources goods and materials renewable resource utilization such as transformer, isolating switch, steel-cored aluminium strand is worth is scrapped by power grid enterprises, should according to national standard and manufacturing process requirement, the accounting of the material such as copper, aluminium, iron and steel or weight in assessment regenerated resources goods and materials.To control regenerated resources market supply and demand market on the other hand in good time, expand information channel, strengthen information data and extract, process, analyze and judge, search the potential rule of price volalility, ensure that price potential measuring and calculating is had proof and evidence, had sufficient grounds.
Existing Forecasting Methodology mainly contains two kinds: empirical method and gravimetric method.Empirical method, makes supposition by staff according to the value of history goods and materials, gravimetric method, according to the weight of goods and materials, by heavily determining the price.Regenerated resources price of material has itself the feature of uncertainty, multi-selection, add the special nature of electrical network goods and materials and skimble-scamble technical standard, because valuation personnel are different to the familiarity of different goods and materials, and the quality of appraiser is uneven, inevitably there will be the factor that some are in the valuation of regenerated resources goods and materials, its objective and accurate property can not be ensured; Secondly, be limited by the impact of raw material market price, social economy's prosperity degree and supplydemand relationship, regenerated resources recycle market price fluctuations is larger, lack regenerated resources recycle market price information collection work mechanism and trend prediction methods, be difficult to ensure the accuracy of regenerated resources goods and materials price potential and the success ratio of web teaching system; 3rd, there is manual intervention phenomenon in some regional bid markets, this not only runs counter to the objective law of market economy and the relevant regulations of bid, and brings negative effect can to the enterprise participating in bid.
Summary of the invention
The invention provides a kind of power grid enterprises' regenerated resources price evaluation method based on social fair value, by the assessment of strengthening inherent value and outside price expectation, the regenerated resources goods and materials based on fair value of constructing system dispose price potential Calculating model, and the application of Valuation Modelling is by the lifting of the efficiency and management effect that greatly improve power grid enterprises' regenerated resources disposing task.
For solving the problems of the technologies described above, the present invention adopts following technical scheme:
Based on power grid enterprises' regenerated resources price evaluation method of social fair value, comprise the steps:
(1) choose base year, read the interval futures price of regenerated resources goods and materials of power grid enterprises' regenerated resources trade market historical sample and the historical price same period of spot price and regenerated resources goods and materials;
(2) the inherent value assessment models of regenerated resources goods and materials is set up based on regression model:
(21) if regenerated resources goods and materials are material type, then the modeling of density hydrometer method is adopted;
Described density hydrometer method, according to the kind of heavy metal in material type regenerated resources goods and materials, is divided into single material and mixed materials two kinds of Valuation Modelling;
The formula of described single material Valuation Modelling is as follows:
P＝αρSLp
Wherein P is the price potential of regenerated resources goods and materials, and p is material reference price (yuan/ton), and S is material cross section (mm
2), ρ is material density (g/cm
3), L is material length (km), α is regression coefficient;
The formula of described composite Valuation Modelling is as follows:
P＝P
1+…+P
m＝G
1p
1+…+G
mp
m
Wherein P
ithe value of often kind of material, G
ithe weight of often kind of material, p
iit is the price of often kind of material;
(22) if regenerated resources goods and materials are equipment class, then adopt and manufacture the modeling of quota estimation algorithm;
Described manufacture quota estimation algorithm uses principal component analytical method, is worth maximally related some questions, uses correlation analysis and regression analysis to set up Valuation Modelling based on regenerated resources goods and materials;
(3) trend model of regenerated resources goods and materials Valuation Modelling is obtained by time difference and regression prediction method:
(31) if regenerated resources price of material affects by regenerated resources goods and materials spot price and futures price, and the change of the slightly delayed futures market of the price in regenerated resources market and spot market, the fluctuation then introducing regenerated resources goods and materials futures price and spot price obtains the trend model of regenerated resources goods and materials Valuation Modelling, and formula is as follows:
Wherein p
i+1for material is in the forecast price of regenerated resources trade market future time point, p
i' for current point in time material is in the knockdown price of regenerated resources trade market,
for current point in time comparatively goes up the fluctuating price of a time point material in futures market,
for current point in time comparatively goes up the fluctuating price of a time point material in spot market, β
1, β
2, β
3for regression coefficient;
(32) if regenerated resources goods and materials not presence commodity price, or time more for equipment class goods and materials material kind, introduce the fluctuation of history knockdown price and new price of material, set up regression model, formula is as follows:
Wherein p
i" be the history knockdown price of regenerated resources goods and materials,
for the fluctuating price of new goods and materials, χ
1, χ
2for regression coefficient;
(4) regenerated resources goods and materials Valuation Modelling application, the accuracy of testing model.
The material parameters of regenerated resources goods and materials involved in above-mentioned steps (2) obtains by regenerated resources material information database, the foundation of this regenerated resources material information database is by gathering producer's gross data of regenerated resources goods and materials, collect and improve the parameter information of the concrete material of all kinds of regenerated resources goods and materials, and then progressively set up and safeguard this database.
Preferably, two times are chosen as base year.
From above technical scheme, the present invention has following beneficial effect:
Set up a power grid enterprises' regenerated resources price evaluation model based on fair value, based on the inherent value of regenerated resources goods and materials, periodic collection relevant market information and pricing information, take into full account the recovery market factor, set up data model, effective prediction markets tendency, the string mark phenomenon of failing to be sold at auction because price deviation causes more greatly can be reduced, valuation price can be prevented to be less than actual value simultaneously, cause economic loss; By checking that is theoretical and true fetched data, indicate the reliability of Calculating model and can operate, to national grid or other industry, as mining industry and building industry, the value assessment of its regenerated resources goods and materials has higher theory and practice to be worth.
Embodiment
The present invention is by the assessment of strengthening inherent value and outside price expectation, the recycling of recyclable waste price evaluation method based on fair value of constructing system, the present embodiment is specifically for the unit take-back cost appraisal procedure of power grid enterprises' regenerated resources goods and materials, is described in detail below to the specific embodiment of the present invention.
The theory obtaining electrical network major equipment from supplier and technician disassembles data, from 2012 to 2014, state's net Anhui Company Electronic business platform regenerated resources goods and materials dispose total 23 events, and the data of 267 auction mark bags obtain as model parameter and the data of checking.Consider value and the treatment capacity of regenerated resources goods and materials, find that transformer, steel-cored aluminium strand, aluminum stranded conductor, cable are the main regeneration resource goods and materials of electrical network process, and be worth larger.Therefore the present embodiment will be main for these goods and materials, analyze the modeling process of Valuation Modelling.
Step (1), collect from 2012 2014 major metals as the futures price of copper, aluminium, iron and steel etc. and spot price, and collect the historical price same period of main regeneration resource goods and materials of Chinese zones of different, different industries from platforms such as Chinese regenerated resources net, Alibaba.
Step (2), sets up the inherent value assessment models of regenerated resources goods and materials.
Need the inherent value assessment models corresponding according to the type selecting of regenerated resources goods and materials, first judge regenerated resources goods and materials type and feature, wherein regenerated resources goods and materials that are valueless or low value are directly given up, and important or high value goods and materials segment further again.
The main regeneration resource goods and materials of power grid enterprises' recoverable are divided into material type (regenerated resources cable, steel-cored aluminium strand etc.) and equipment class (transformer, isolating switch etc.), the difference of the factor such as material kind, material properties and material price change of different classes of regenerated resources goods and materials because affecting it and being worth, its Valuation Modelling is also not quite similar.
If regenerated resources goods and materials are material type, then adopt the modeling of density hydrometer method, if regenerated resources goods and materials are equipment class, then adopt and manufacture the modeling of quota estimation algorithm.
According to the kind of heavy metal in material type regenerated resources goods and materials, density hydrometer method is divided into again single material and mixed materials two kinds of computation models.
Single material: for the regenerated resources goods and materials of single material, as copper cash, aluminum stranded conductor etc., finds the factor relevant to its value.This kind of goods and materials raw material ratio is simply clear, affects larger by the prices of raw and semifnished materials.Inspection finds that the value of homogenous material class regenerated resources goods and materials and material weight, price, total price are all positively related, and almost reach 1 with the correlativity that material is worth, and material total price and material weight and material price present strong correlation, Modling model accordingly, formula is as follows:
P＝αρSLp
Wherein P is the price potential of regenerated resources goods and materials, and p is material reference price (yuan/ton), and S is material cross section (mm
2), ρ is material density (g/cm
3), L is material length (km), α is regression coefficient.
Composite: the goods and materials estimation method of similar single material, its quality of regenerated resources goods and materials of mixed materials is made up of the material of different kinds, and the price level of unlike material is also different, the weight of its price and often kind of material, price and total price are all strong correlations, and material total price is extremely strong relevant to material weight and material price, by cumulative Modling model, formula is as follows:
P＝P
1+…+P
m＝G
1p
1+…+G
mp
m
Wherein P
ithe value of often kind of material, G
ithe weight of often kind of material, p
iit is the price of often kind of material.
The heavy estimation method of density ratio, is applicable to the disposal price potential measuring and calculating of the materials such as regenerated resources cable, steel-cored aluminium strand.Mainly according to the density of copper, aluminium, iron and steel, converse the weight of cable or all kinds of material proportion, then draw price potential according to market reference valency.The Weight computation of regenerated resources goods and materials, technical parameter all uses theoretical value.
The described estimation algorithm by norm that manufactures is the regenerated resources goods and materials for the complex apparatus such as transformer, isolating switch class, its raw material ratio kind is more, so need to use principal component analytical method, need find and be worth maximally related some questions with regenerated resources goods and materials, and then use correlation analysis and regression analysis to set up Valuation Modelling.
For transformer, with transformer be worth related coefficient be greater than 0.5 be the factor of strong correlation, filter out strong correlation factor totally 4, i.e. heavy, the iron and steel of gross weight of equipment, oil and copper.But gross weight of equipment depends on oil weight, iron and steel and copper, through principal component analysis (PCA), finally leaves three strong correlation factors, use regression technique to obtain its Valuation Modelling, formula is as follows:
P
always=G
copper× p
copper+ G
iron and steel× p
iron and steel
Wherein, G is material gross weight, and p is material reference price.
During model valuation, by actual analysis, the gross data of equipment class transformer and actual to disassemble gap data little, therefore replace actual value when valuation by gross data, the transformer of different model and producer is unified.
The material parameters of regenerated resources goods and materials involved in above-mentioned steps, need the parameter descriptor of the concrete material understanding material class and equipment class goods and materials, the application of Valuation Modelling depends on the order of accuarcy of goods and materials material parameters.In model practical application, by disassembling analysis and measurement, can replace actual disassembling data by the producer gross data of regenerated resources goods and materials.Therefore in practical application, by constantly collecting and improve the parameter information of all kinds of regenerated resources goods and materials, progressively set up and safeguard regenerated resources material information database, to realize valuation function.
Step (3), adds market data and carries out trend analysis.
In regenerated resources goods and materials inherent value assessment models, material weight does not change in time, and material price constantly changes along with the change of time, market.Only have and suitable judgement is made to the price of material, Valuation Modelling just can be made to play its maximum effect; For the regenerated resources goods and materials of not presence commodity price, with regard to regenerated resources goods and materials itself, its value can be subject to the impact of history knock-down price, new price of material level etc.Above-mentioned by time difference and regression forecasting, obtain price expectation model, set up the trend model of regenerated resources goods and materials Valuation Modelling.
For the situation that regenerated resources price of material affects by goods and materials spot price and futures price, the slightly delayed futures market of price in its regenerated resources market and the change of spot market, the fluctuation then introducing regenerated resources goods and materials futures price and spot price obtains the trend model of regenerated resources goods and materials Valuation Modelling, and formula is as follows:
Wherein p
i+1for material is in the forecast price of regenerated resources trade market future time point, p
i' for current point in time material is in the knockdown price of regenerated resources trade market,
for current point in time comparatively goes up the fluctuating price of a time point material in futures market,
for current point in time comparatively goes up the fluctuating price of a time point material in spot market, β
1, β
2, β
3for regression coefficient.
And some regenerated resources goods and materials not presence commodity price, or time more for equipment class goods and materials material kind, the fluctuation of its history knockdown price and new price of material can be considered, introduce the fluctuation of history knockdown price and new price of material, set up regression model, formula is as follows:
Wherein p
i" be the history knockdown price of regenerated resources goods and materials,
for the fluctuating price of new goods and materials, χ
1, χ
2for regression coefficient.
Step (4), regenerated resources goods and materials Valuation Modelling is applied, the accuracy of testing model.
Because what final web teaching system struck a bargain is whole mark bag, average price is only had not have the price of single goods and materials, therefore suppose that the historical evaluation valency of certain goods and materials is x, belonging to it, the historical evaluation valency of bag is A, history knock-down price is B, then the estimation equation of the history knock-down price of these goods and materials is: y=x*B/A, then uses history fetched data to carry out regretional analysis, finally obtains the raw-material price formulae of regenerated resources goods and materials.
According to above analysis, respectively to a few class goods and materials that electrical network web teaching system is main, steel strand wires, steel-cored aluminium strand and 10kV transformer are analyzed.Following table 1 is the steel strand wires model valuation interpretation of result adopting single material density hydrometer method, and table 2 is the steel-cored aluminium strand model valuation interpretations of result adopting composite density hydrometer method, and table 3 manufactures quota method transformer model valuation interpretation of result, specific as follows:
| Specifications and models | Quantity | Unit | Inherent value | Valuation | Former assessment valency | Knock-down price | Error | Former error | Accuracy rate improves |
| GJ-35 | 0.145 | Ton | 304.3 | 289.1 | 290 | 397.36 | 108.27 | 107.36 | -0.23％ |
| GJ-35 | 0.12 | Ton | 229.94 | 218.63 | 200 | 265.89 | 47.26 | 65.89 | 7.01％ |
| GJ-35 | 0.532 | Ton | 1067.93 | 1015.21 | 1000 | 1136.23 | 121.02 | 136.23 | 1.34％ |
| GJ-35 | 0.12 | Ton | 197.09 | 187.25 | 160 | 176.9 | -10.36 | 16.9 | 15.41％ |
| GJ-35 | 2.3 | Ton | 4617.01 | 4385.2 | 4300 | 5007.41 | 622.21 | 707.41 | 1.70％ |
| GJ-50 | 0.56 | Ton | 1121.88 | 1065.81 | 1200 | 1397.31 | 331.5 | 197.31 | -9.60％ |
| GJ-35 | 0.13 | Ton | 213.51 | 203.03 | 169 | 189.16 | -13.87 | 20.16 | 17.99％ |
Table 1
Table 2
Table 3
As seen from the above table, compared with original valuation mode, accuracy is greatly improved, and formulates reserve price provide foundation for science, and in order to promote, regenerated resources goods and materials are manipulated so power, anti-scope mark string bid behavior provides important guarantee.
Models applying example:
Below with State Grid Anhui Electric Power Company's the 10th batch of regenerated resources goods and materials web teaching system bag 4 in 2014 for sample, carry out the analysis of Valuation Modelling practical application.
(1) regenerated resources regenerated resources price of material
Choose domestic representative regional regenerated resources regenerated resources price of material, calculate current price, with October 31 for data acquisition market day.Regenerated resources price of material is originated: Chinese scrap metal (http://jinshu.feijiu.net/)
(2) goods and materials futures price
Use Shanghai copper index (CUL9) and Shanghai aluminum index (ALL9) respectively, calculate the futures price of copper and aluminium, because futures'price is comparatively large, so go the futures price of valuation the last week to take the mean.Data Source: state unit navigator quotation system.
(3) goods and materials spot price
Spot-market price is calculated with spot market, Shanghai copper and aluminium.Data Source Shanghai non-ferrous metal net (http://www.smm.cn/), middle aluminium net (http://www.cnal.com/)
Comprehensive above Data Source, in conjunction with problem theoretical research valuation regression coefficient, draw the reference price of the current regenerated resources goods and materials of Valuation Modelling, formula is as follows:
P
materialfor regenerated resources goods and materials material price;
P
ifor current point in time material is in the average knockdown price in regenerated resources market;
for current point in time material is in the price of futures market;
for current point in time material is in the price of spot market.
Wherein the price value of copper is:
P
copper=0.95*29662.5+0.02*47527.14+0.03*48138.57=30574.085
The price value of aluminium is:
P
aluminium=0.95*10525+0.02*13860+0.03*13632.86=10684.94
The price value of iron and steel is the average price of regenerated resources iron and steel, namely
P
steel=1837.5
(4) cable goods and materials valuation
The steel-cored aluminium strand model of wrapping 4 Lingbi companies in this selected sample is: LGJ-16, according to the density of copper, aluminium, iron and steel and the area proportion of LGJ-16 steel-cored aluminium strand, converses the weight proportion of steel-cored aluminium strand, namely
S
aluminium/ S
steel=16.13/2.69
Carry out weight conversion, namely
G
aluminium/ G
steel=16.13*2.7/2.69*7.8=2.076
That is, the heavy accounting 67% of LGJ-16 steel core aluminum stranded conductor aluminium, the heavy accounting 33% of steel.
(5) Valuation Modelling of transformer:
P
always=G
copper× p
copper+ G
iron and steel× p
iron and steel, only calculate the value of copper and iron and steel two kinds of materials.
(6) Valuation Modelling applicating evaluating is analyzed
Apply new Valuation Modelling and carry out valuation to main equipment and cable, new model valuation result, can the market fair value of relatively accurate embodiment regenerated resources goods and materials substantially between former valuation and knock-down price, as shown in table 4.Meanwhile, because new model valuation more levels off to knock-down price, therefore, predict the knock-down price of following regenerated resources goods and materials with new model valuation when valuation, be conducive to the setting of the control of subpackage mark bag value size and reserve price, trigger price.
Table 4
The above embodiment is only be described the preferred embodiment of the present invention; not scope of the present invention is limited; under not departing from the present invention and designing the prerequisite of spirit; the various distortion that those of ordinary skill in the art make technical scheme of the present invention and improvement, all should fall in protection domain that claims of the present invention determine.
Claims (3)
1., based on power grid enterprises' regenerated resources price evaluation method of social fair value, it is characterized in that, comprise the steps:
(1) choose base year, read the interval futures price of regenerated resources goods and materials of power grid enterprises' regenerated resources trade market historical sample and the historical price same period of spot price and regenerated resources goods and materials;
(2) the inherent value assessment models of regenerated resources goods and materials is set up based on regression model:
(21) if regenerated resources goods and materials are material type, then the modeling of density hydrometer method is adopted;
Described density hydrometer method, according to the kind of heavy metal in material type regenerated resources goods and materials, is divided into single material and mixed materials two kinds of Valuation Modelling;
The formula of described single material Valuation Modelling is as follows:
P＝αρSLp
Wherein P is the price potential of regenerated resources goods and materials, and p is material reference price (yuan/ton), and S is material cross section (mm
2), ρ is material density (g/cm
3), L is material length (km), α is regression coefficient;
The formula of described composite Valuation Modelling is as follows:
P＝P
1+…+P
m＝G
1p
1+…+G
mp
m
Wherein P
ithe value of often kind of material, G
ithe weight of often kind of material, p
iit is the price of often kind of material;
(22) if regenerated resources goods and materials are equipment class, then adopt and manufacture the modeling of quota estimation algorithm;
Described manufacture quota estimation algorithm uses principal component analytical method, is worth maximally related some questions, uses correlation analysis and regression analysis to set up Valuation Modelling based on regenerated resources goods and materials;
(3) trend model of regenerated resources goods and materials Valuation Modelling is obtained by time difference and regression prediction method:
(31) if regenerated resources price of material affects by regenerated resources goods and materials spot price and futures price, and the change of the slightly delayed futures market of the price in regenerated resources market and spot market, the fluctuation then introducing regenerated resources goods and materials futures price and spot price obtains the trend model of regenerated resources goods and materials Valuation Modelling, and formula is as follows:
Wherein p
i+1for material is in the forecast price of regenerated resources trade market future time point, p '
ifor current point in time material is in the knockdown price of regenerated resources trade market,
for current point in time comparatively goes up the fluctuating price of a time point material in futures market,
for current point in time comparatively goes up the fluctuating price of a time point material in spot market, β
1, β
2, β
3for regression coefficient;
(32) if regenerated resources goods and materials not presence commodity price, or time more for equipment class goods and materials material kind, introduce the fluctuation of history knockdown price and new price of material, set up regression model, formula is as follows:
Wherein p "
ifor the history knockdown price of regenerated resources goods and materials,
for the fluctuating price of new goods and materials, χ
1, χ
2for regression coefficient;
(4) regenerated resources goods and materials Valuation Modelling application, the accuracy of testing model.
2. power grid enterprises according to claim 1 regenerated resources price evaluation method, it is characterized in that, the method also comprises the producer's gross data gathering regenerated resources goods and materials, collect and improve the parameter information of the concrete material of all kinds of regenerated resources goods and materials, set up and safeguard regenerated resources material information database.
3. power grid enterprises according to claim 1 regenerated resources price evaluation method, is characterized in that, in step (1), chooses two times as base year.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510336694.0A CN104915785B (en) | 2015-06-16 | 2015-06-16 | Power grid enterprises' regenerated resources price evaluation method based on social fair value |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510336694.0A CN104915785B (en) | 2015-06-16 | 2015-06-16 | Power grid enterprises' regenerated resources price evaluation method based on social fair value |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104915785A true CN104915785A (en) | 2015-09-16 |
| CN104915785B CN104915785B (en) | 2018-06-19 |
Family
ID=54084832
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510336694.0A Active CN104915785B (en) | 2015-06-16 | 2015-06-16 | Power grid enterprises' regenerated resources price evaluation method based on social fair value |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104915785B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111241483A (en) * | 2019-01-11 | 2020-06-05 | 深圳联合产权交易所股份有限公司 | Resource value evaluation processing method based on cloud platform and related products |
| CN117474531A (en) * | 2023-12-27 | 2024-01-30 | 他山互联网科技(三明)有限公司 | Renewable resource industry service system based on block chain |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1472652A (en) * | 2003-07-17 | 2004-02-04 | 中国科学院计算技术研究所 | Software breakdown testing method for dynamic resouce management |
| US20040215529A1 (en) * | 2004-04-16 | 2004-10-28 | Foster Andre E. | System and method for energy price forecasting automation |
| CN102646217A (en) * | 2011-02-21 | 2012-08-22 | 中国地质科学院矿产资源研究所 | Method for predicting recovery amount of aluminum metal secondary resources |
-
2015
- 2015-06-16 CN CN201510336694.0A patent/CN104915785B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1472652A (en) * | 2003-07-17 | 2004-02-04 | 中国科学院计算技术研究所 | Software breakdown testing method for dynamic resouce management |
| US20040215529A1 (en) * | 2004-04-16 | 2004-10-28 | Foster Andre E. | System and method for energy price forecasting automation |
| CN102646217A (en) * | 2011-02-21 | 2012-08-22 | 中国地质科学院矿产资源研究所 | Method for predicting recovery amount of aluminum metal secondary resources |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111241483A (en) * | 2019-01-11 | 2020-06-05 | 深圳联合产权交易所股份有限公司 | Resource value evaluation processing method based on cloud platform and related products |
| CN117474531A (en) * | 2023-12-27 | 2024-01-30 | 他山互联网科技(三明)有限公司 | Renewable resource industry service system based on block chain |
| CN117474531B (en) * | 2023-12-27 | 2024-03-19 | 他山互联网科技(三明)有限公司 | Renewable resource industry service system based on block chain |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104915785B (en) | 2018-06-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107123982B (en) | Power distribution network reliability economic benefit analysis method based on equipment transaction | |
| Wu et al. | An integrated decision-making model for sustainable photovoltaic module supplier selection based on combined weight and cumulative prospect theory | |
| Zaman et al. | Performance evaluation and benchmarking of global waste management systems | |
| Shi et al. | A decision support system to select suppliers for a sustainable supply chain based on a systematic DEA approach | |
| Zhu et al. | Relocation or reallocation: Impacts of differentiated energy saving regulation on manufacturing industries in China | |
| CN109272140B (en) | Big data analysis-based power transformation equipment operation period cost prediction method | |
| CN107194536A (en) | The power supply reliability negative benefit appraisal procedure and device of a kind of project investment | |
| Yang et al. | Optimal investment decision of distribution network with investment ability and project correlation constraints | |
| CN104915785A (en) | Power grid enterprise renewable resource price evaluation method based on social fair value | |
| Barbini et al. | Integration of life cycle data in a BIM object library to support green and digital public procurements | |
| Lee et al. | Development of assessment model for demand-side management investment programs in Korea | |
| CN109255470B (en) | Power transformation equipment non-project cost prediction method based on big data analysis | |
| CN115018311A (en) | Method, system, equipment and medium for multi-dimensional potential depiction evaluation of power industry users | |
| CN107909477B (en) | Power transmission network planning project investment combination optimization method | |
| Yin et al. | Sustain China's copper resources with domestic mining, trading, and recycling | |
| CN105809283A (en) | Comprehensive quantitative evaluation method for calculating influence degree of external economic elements on provincial level power utilization market | |
| Atiya et al. | AN OPTIMIZATION OF PRODUCT DESIGN AND MANUFACTURING BASED ON SUSTAINABILITY. | |
| Sakthivel et al. | Strategies for Quantifying Metal Recovery from Waste Electrical and Electronic Equipment (WEEE/E-waste) Using Mathematical Approach | |
| by Kernel | Bohong Wang), Tian Xia, and Qinglai Guo Department of Electrical Engineering, Tsinghua University, Beijing 100084, China wbh19@ mails. tsinghua. edu. cn, guoqinglai@ tsinghua. edu. cn | |
| Xin et al. | Research on Information Price of Prefabricated Power Equipment and Materials | |
| Niu et al. | Power grid construction project cost risk factors analysis based on the fishbone diagram theory | |
| Ma et al. | Exploration on Prediction and Early Warning Technology for Investment Completion of 10 kV And Below Power Grid Infrastructure Projects | |
| Bai et al. | Electricity market liberalization under the power of customer value evaluation and service model | |
| Qi | Research on the Application of Activities-Based Cost Method in L Manufacturing Enterprise | |
| Ji et al. | Distributed Photovoltaic Market Demand Analysis Based on Market Segmentation Theory |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |